AI/ML Infrastructure Software Engineer

AI/ML Infrastructure Software Engineer _corporate_fare_ Google _place_ Bengaluru, Karnataka, India **Advanced** Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain. **Minimum qualifications:** + Bachelor's degree or equivalent practical experience. + 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript). + Experience in ML Infrastructure Development or ML Performance Engineering. **Preferred qualifications:** + Experience with Machine Learning (ML) development process. + Expertise in C++ and Python, Responsible ML, ML Explainability, ML Fairness Tensorflow , JAX, Keras, Gemax TFX, TFlex, Xflow or ML Performance Engineering. + Knowledge of Google production infrastructure. + Ability to collaborate with partners on applying ML to their use cases. + Passion for building infrastructure to increase the velocity of ML development. **About the job** The AI Flow Platform and suite of products are used by thousands of Googlers across all product areas to drive business impact for Google in innumerable ways (e.g., finding insights in data, building classical ML models, experimenting with Gemini, and more). Our team provides a dependable, compliant, and scalable platform that enables product teams to iterate rapidly on new ideas and to take the best ideas for production. In this role, you will have an opportunity to influence the future of applied ML at Google, pushing the boundaries of what teams can achieve with generative and discriminative technologies, leaving a lasting impact on the field. **Responsibilities** + Develop and maintain our production service, written in C++ and Python, and further the platform goal of incorporating prompt optimization, fine tuning, hyperparameter optimization, and ML best practices into Google product development. + Design and implement customer requested ML and AI features end-to-end from requirements-gathering and design-authoring, through implementation and landing impact in production. + Explore charter expansion based on next-generation product requirements from internal and external customers. 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